Hamming AI
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About
Hamming AI serves as a comprehensive quality assurance platform tailored specifically for the complexities of voice and chat AI agents. As businesses increasingly deploy LLM-powered voice agents for high-stakes tasks, the need for rigorous, automated validation becomes critical. Hamming addresses this by providing an end-to-end environment that spans from initial development and pre-launch stress testing to continuous production monitoring. Unlike manual QA, which is difficult to scale and prone to inconsistency, this platform allows teams to simulate thousands of diverse conversational scenarios to catch hallucinations and prompt regressions before they impact the end user. The platform operates on a developer-first, API-centric model. This architecture enables engineering teams to programmatically trigger test suites, fetch results, and integrate QA directly into their existing CI/CD pipelines using tools like GitHub Actions or Jenkins. Users can take advantage of auto-generated test scenarios or define custom multi-turn flows to evaluate how an agent handles complex logic, such as appointment scheduling across time zones or handling dietary restrictions in a drive-thru setting. Evaluation is conducted using over 50 distinct metrics that analyze not just the transcript, but also factors like sentiment, adherence to instructions, and conversational fluidity. Hamming is particularly valuable for industries where reliability and compliance are non-negotiable, such as healthcare, finance, and enterprise customer service. For healthcare providers, the platform is HIPAA-compliant and supports the signing of Business Associate Agreements (BAAs), ensuring that agents handling protected health information (PHI) are tested within a secure framework. It also helps financial institutions maintain strict governance by monitoring for PII leakage and off-script behavior. With support for over 65 languages and various regional accents—including South Indian, Gulf Arabic, and Australian English—it is designed for global organizations that need to ensure their agents perform consistently across different demographics. What distinguishes Hamming from general-purpose LLM monitoring tools is its deep focus on the unique challenges of voice, such as latency and interruptions. It provides detailed performance analytics, measuring p50 and p90 Time to First Word (TTFW) to identify latency spikes that could frustrate callers. Additionally, the platform allows for "red-teaming" to test agent boundaries and the ability to replay real production calls for regression testing. This ensures that every iteration of a system’s prompt or model improves the overall user experience without introducing new, unforeseen errors.
Pros & Cons
Supports over 65 languages and specific regional accents for global agent deployment.
Certified SOC 2 Type II and HIPAA compliant with BAA availability for regulated industries.
Provides deep latency analytics including p50 and p90 Time to First Word (TTFW) measurements.
API-first architecture allows for seamless integration into existing CI/CD pipelines.
Enables high-scale load testing to identify bottlenecks before they affect real users.
Specific pricing details are not available on the website and require booking a demo.
The focus on high-stakes, multi-language voice may be excessive for simple text-only chat projects.
Use Cases
Backend Engineers can trigger automated test suites via API on every deploy to block bad prompt changes from reaching production.
Healthtech companies can use HIPAA-compliant simulations to test patient appointment follow-up agents for accuracy and empathy.
Customer Support Leads can monitor live calls to detect when AI agents fail to escalate emotional conversations to human representatives.
Retail Drive-thrus can simulate rush hour noise and diverse accents to ensure order accuracy in high-volume environments.
Fintech Compliance Officers can run red-team simulations to verify that voice agents are not leaking PII or violating banking regulations.
Platform
Task
Features
• 65+ language support
• api-first integration
• continuous production monitoring
• regression testing for prompt changes
• soc 2 type ii & hipaa compliance
• load testing (1000s of concurrent calls)
• regional accent simulation
• automated pre-launch testing
FAQs
How does Hamming evaluate voice calls?
Hamming uses holistic evaluation across 50+ different metrics rather than simple exact matching. This allows the platform to assess call quality, sentiment, and instruction adherence more accurately.
What languages and accents are supported?
The platform supports over 65 languages and various regional accents, including South Indian, Gulf Arabic, UK English, and Australian English, to simulate real-world user interactions.
Can Hamming test for voice interruptions?
Yes, Hamming is designed to test barge-in capabilities and how well an agent handles being interrupted or navigating complex turn-taking in a conversation.
Is Hamming compliant for use in healthcare?
Yes, Hamming is HIPAA-compliant and can provide a Business Associate Agreement (BAA) for teams testing voice agents that handle protected health information.
How does Hamming integrate with developer workflows?
Hamming is API-first, allowing teams to programmatically trigger tests and fetch results within CI/CD pipelines like GitHub Actions or Jenkins.
Can I use Hamming to monitor live production agents?
Yes, Hamming provides continuous production monitoring to track real-time performance, detect latency spikes, and identify when agents go off-script.
What scale of load testing can the platform handle?
Hamming can simulate thousands of concurrent calls, helping teams identify scalability issues and ensure agents remain performant under heavy production load.
Pricing Plans
Enterprise
Unknown Price• SOC 2 Type II compliance
• HIPAA BAA
• Custom metrics
• Priority support
• Load testing at scale
Job Opportunities
Tech Lead
Ensure the reliability of AI voice agents with automated end-to-end testing, production monitoring, and support for 65+ languages and regional accents.
Experience Requirements:
6 - 10 years leading 3 - 6 engineer pods in high-availability, high-frequency deploy shops
Experience building and operating realtime/distributed systems (workflow engines, WebRTC/telephony, large fan-out queues)
Other Requirements:
TypeScript/Node.js
Python
AWS
Terraform
Kubernetes
OpenTelemetry
SigNoz
Responsibilities:
Technical direction across the stack - backend, frontend, and infra
Team leadership: unblock engineers, set clear priorities, run lightweight design reviews
System reliability: ensure platform stays fast, observable, and stable
Hands-on delivery: contribute to key projects weekly
Cross-functional glue: keep product and operations connected
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Senior/Staff Backend Engineer
Ensure the reliability of AI voice agents with automated end-to-end testing, production monitoring, and support for 65+ languages and regional accents.
Experience Requirements:
Senior/staff experience running distributed backends with real-time/streaming constraints
Shipped production LLM apps
Understanding of prompt/tool design, evals, and guardrail instrumentation
Other Requirements:
TypeScript/Node.js
Python
Temporal
Redis
PostgreSQL
AWS
Terraform
Kubernetes
Responsibilities:
Own core services in TypeScript/Node.js and Python
Scale platform for 10K parallel calls with 99.99% uptime
Harden pipelines for ingestion, evaluation, and analytics
Level-up observability using OpenTelemetry/SigNoz
Prototype, test, and ship new LLM-driven behaviors
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Product Engineer
Ensure the reliability of AI voice agents with automated end-to-end testing, production monitoring, and support for 65+ languages and regional accents.
Experience Requirements:
3+ years building customer-facing products in a high-velocity environment
Other Requirements:
Fluent in TypeScript
React/Next.js
Node services
Responsibilities:
Own product features end-to-end: spec, prototype, ship, iterate
Work closely with customers to drive adoption and outcomes
Build core customer workflows for voice-agent QA
Turn messy, high-dimensional data into product experiences
Maintain high engineering velocity while keeping craftsmanship
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